Rocky Mountain Strategy helps organizations design, build, and deploy AI systems that cut costs, unlock operational efficiency, and create durable competitive advantage—without burning your team out chasing the wrong use cases.
We specialize in practical AI: internal copilots, search & retrieval (RAG), and automated workflows tailored to your actual systems and constraints.
We help you move beyond vague “AI initiatives” into specific, measurable projects that map directly to cost, throughput, and risk. Start with a roadmap—end with deployed systems.
We partner with leadership and domain experts to identify where AI can actually move the needle—then prioritize initiatives based on ROI, technical feasibility, and change impact.
Build private, secure AI assistants on top of your existing knowledge: policies, procedures, tickets, wikis, contracts, and more—so your team gets accurate answers grounded in your data.
We design and implement end-to-end AI workflows: from triaging inbound requests to drafting responses, summarizing tickets, preparing reports, and orchestrating repetitive processes.
We’re not here to sell you another buzzword. Our approach is grounded in your systems, constraints, and risk appetite—delivering concrete wins fast, then expanding from there.
We interview stakeholders, map processes, and inventory the systems and data that matter most. Together we identify a short list of high-leverage AI use cases aligned with your goals.
For the top use cases, we design target architectures: RAG, agents, or automation pipelines. We then stand up a prototype so your team can see and critique the workflow, not just read a slide.
We implement the pipeline: ingestion, retrieval, LLM orchestration, tools, authentication, and observability. Everything is wired into your existing tools—no context-swapping for your team.
Once live, we track adoption, quality, and impact: time saved, tickets resolved, accuracy metrics, and user feedback. Then we iterate: tuning prompts, search, and UX to keep improving outcomes.
These are representative examples of the kind of outcomes AI systems can drive when they’re tightly aligned to real workflows and constraints. Your version will look different—but it should be just as tangible.
A private AI assistant built on policies, procedures, and past tickets answers “how do I…?” questions for support and field teams—in their chat tool of choice. Fewer escalations, faster onboarding, and less time lost hunting across systems.
Result: 30–40% reduction in time spent searching for answers.
AI copilots grounded in official policies and contracts help staff draft responses, summarize changes, and check for compliance issues, while surfacing citations and links back to source documents.
Result: Faster, more consistent responses without sacrificing oversight.
Incoming requests are automatically classified, summarized, and routed; draft replies are generated for human review. Knowledge from prior tickets and docs informs each step.
Result: Meaningful reduction in manual triage and context-switching.
Rocky Mountain Strategy blends hands-on engineering experience with the ability to work directly with business stakeholders. We live at the intersection of data, infrastructure, and day-to-day workflows.
We’ve seen both sides of AI: the glossy demo that never ships, and the quiet internal system that quietly changes how work gets done. We’re firmly in the second camp.
Share a bit about your organization and what you’re exploring. We’ll follow up with a short intro call to see if we’re a fit—no pressure, no obligation.
Great starting points: “We want an internal AI assistant for X,” “We’re trying to reduce time spent on Y,” or “We need help turning AI ideas into a concrete plan.”